Artificial selection also plays a significant role in improving molecular functions through experimental directed evolution. Importantly, directed evolution in the lab is currently being employed to improve the activity and selectivity of molecules and enzymes [1]}, [2]}, [3]}, often desirable in industry or for pharmaceutical purposes. For example, experimental techniques like morbidostat have been designed to directly measure the growth rate of evolving microbial populations and accordingly tune the strength of selection induced by antibiotics in order to achieve continuous drug-induced inhibition in an experimental setup [4]}, [5]}. More recently, control protocols, such as proportional-integral-derivative control [6]}, have been experimentally implemented in high-throughput continuous directed evolution of proteins to automatically tune artificial selection based on the state of the population and optimize function [7]}, [8]}, [9]}. Implementing optimal control in these automated and continuous directed evolution experiments will have significant impact in efficiently synthesizing molecules with desired function.
